The Refugee Law Lab is looking for students with strong Python, data scraping and data wrangling skills to help with natural language processing projects involving legal data.
Two part-time positions are open to York University undergraduate students in data science, computer science, software engineering or related disciplines.
The Lab has secured funding to build a free open-source legal analytics application in the refugee law field. The application uses data about Canada’s refugee determination process scraped from online sources, applies various NLP tools to extract useful information from that data, and then presents analysis of that data to assist refugee lawyers appearing before the Immigration and Refugee Board and the Federal Court.
To assist with this project, the successful candidates will:
(a) Participate in brainstorming and planning meetings
(b) Program automated processes for legal data collection from online sources
(c) Undertake data wrangling to clean the collected data
(d) Assist with applying NLP categorization tools on the data
Qualifications & Competencies:
- Currently enrolled York undergraduate student in a relevant discipline (e.g. data science, computer science, software engineering)
- Strong Python programming skills
- Data scraping / data wrangling experience is an asset
- Experience with natural language processing is an asset
- French language skills are an asset
- Lived experience with forced migration or being a member of an equity seeking group is an asset.
Place of work: remote
Salary: $25/hr (inclusive of vacation pay)
Time Commitment: Approximately 5-7 hours per week throughout the Fall 2022 and Winter 2023 Terms. Hours are flexible and we can accommodate periods of non-availability.
Eligibility: Current York University undergraduate student in 2nd / 3rd / 4th year in Data Science, Computer Science, Software Engineering or related disciplines. Must be eligible for Research at York positions.
Application Deadline: September 12 at 5:00pmET
Application process: Apply online with a CV, electronic copy of unofficial transcripts, and a brief cover note describing your interest in the position.